A low computational complexity normalized subband adaptive filter algorithm employing signed regressor of input signal

A low computational complexity normalized subband adaptive filter algorithm employing signed regressor of input signal

Abstract ᅟ In this paper, the signed regressor normalized subband adaptive filter (SR-NSAF) algorithm is proposed. This algorithm is optimized by L 1-norm minimization criteria. The SR-NSAF has a fast convergence speed and a low steady-state error similar to the conventional NSAF. In addition, the p...

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Bibliographic Details
Main Authors: Mohammad Shams Esfand Abadi, Mohammad Saeed Shafiee, Mehrdad Zalaghi
Format: Article
Language:English
Published: SpringerOpen 2018-04-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Normalized subband adaptive filter (NSAF)
Mean-square performance
Signed regressor (SR)L 1-norm
Online Access:http://link.springer.com/article/10.1186/s13634-018-0542-z

Internet

http://link.springer.com/article/10.1186/s13634-018-0542-z

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